Users have today a possibility to reach and be reached by a vast amount of information on a variety of user devices. Such user devices include telephones, hand-held devices, personal computers (PCs), personal digital assistants (PDAs), and the like. The information may be provided to the user in a push mode, that is, information is provided to the user without a specific action on the user's side. In the push mode, information provided in the form of advertisements is most prominent. On the other hand, information may be provided to a user in a pull mode, that is, the user initiates an action that results with providing of information back to the user.
In order for information provided to the user in either a push or pull mode, it is beneficial to characterize the user using some kind of a user profile. This requires monitoring of the user accessing information and attempting to identify patterns that may be then reduced into certain characteristics of the user, usually referred to as a user profile. A created user profile may be then used to better match the information provided to the user based on the user profile. For example, web sites as well as search engines such as Google®, are known to perform such monitoring by tracking the user either by leaving monitors on the user device or by encouraging the user to log on to the web site, thereby identifying the user. Monitors may be implemented using cookies, which are simple pieces of data that are exchanged between a server and a client, thereby affecting the operation of the web server. Regardless of mode of operation the more information the system attempts to collect about the user the greater the security risk for the user's information, predominantly, the user's privacy. An accurate profile outside of the control of a user may lead to significant privacy breaches that may be detrimental to the user.
Merely collecting information from the user in response, for example, to a questionnaire presented to the user, may be significantly lacking due to inaccuracies and/or the fear of the user from a breach of privacy. Prior art attempts to overcome this drawback by generating clusters of user profiles and fitting a user with other profiles generating a more generic profile of a group of people like the user. However, this may suffer from a significant drawback as this is performed typically on per source, for example, a web site, basis, and does not account for the significant variation even within the group.
Thus, there is a need in the art to overcome the deficiencies of the prior art solutions.